PC-based human face recognition system

Abstract

Measurements from features of a human such as eyes, nose, mouth, and face profile are used for face recognition. Images of human faces, each 256*200 in size with 64 shades of gray, are stored in a gray-level referenced file. Face matchings were performed in two stages. In the first stage, image processing techniques were used to extract six features from each of the gray-level images. Each face is represented by a vector of six dimensions and is stored in the six-feature referenced file along with the gray-level images. The same features from an unlabeled face were then extracted and a search was performed to locate the most likely candidates in the six-feature file. Computations were greatly simplified since matching was based on six numbers and many of the unlikely candidates were eliminated at this stage. The second stage involved the matching of all facial features of the unlabeled face to those of the most likely candidates in the gray-level file. Time required to match a face was greatly reduced since comparison of all facial features was done on relatively fewer most likely candidates. Experimental results indicated that with a small referenced file of ten persons the system was able to correctly classify unlabeled faces 80% of the time. Currently a computing time of 15 minutes is needed for each classification.<>